{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## House price prediction with Concrete ML XGBoost Regressor\n",
    "\n",
    "The XGBoost (Extreme Gradient Boosting) algorithm is one of the most popular algorithms in ML and often the big winner in various kaggle competitions.\n",
    "\n",
    "XGBoost is a supervised machine learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simpler and weaker models.\n",
    "\n",
    "In this notebook, we tackle a privacy-preserving regression task with the XGBoost model from Concrete ML. The data-set used is \"Housing prices\", which contains real-world data.\n",
    "\n",
    "This tutorial shows how to use XGBoost regression with Concrete ML and discusses model parameter choices that enable efficient privacy-preserving inference using FHE.\n",
    "\n",
    "Let's get started."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import libraries\n",
    "\n",
    "First, import the required packages, the classical XGBoost regressor and its Concrete ML counterpart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pylint: disable=too-many-lines,invalid-name\n",
    "import warnings\n",
    "\n",
    "# For warnings in xgboost.sklearn\n",
    "warnings.simplefilter(action=\"ignore\", category=FutureWarning)\n",
    "\n",
    "import time\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn import metrics, preprocessing\n",
    "from sklearn.datasets import fetch_openml\n",
    "from sklearn.model_selection import GridSearchCV, train_test_split\n",
    "from xgboost.sklearn import XGBRegressor as SklearnXGBRegressor\n",
    "\n",
    "from concrete.ml.sklearn import XGBRegressor as ConcreteXGBRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data-set \n",
    "\n",
    "Let's download the data-set from [openml](https://www.openml.org/search?type=data&status=active&id=43926).\n",
    "\n",
    "The goal is to estimate the selling price of houses based on 81 features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape: (2930, 81)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sale_Price</th>\n",
       "      <th>MS_SubClass</th>\n",
       "      <th>MS_Zoning</th>\n",
       "      <th>Lot_Frontage</th>\n",
       "      <th>Lot_Area</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot_Shape</th>\n",
       "      <th>Land_Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>Pool_QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc_Feature</th>\n",
       "      <th>Misc_Val</th>\n",
       "      <th>Mo_Sold</th>\n",
       "      <th>Year_Sold</th>\n",
       "      <th>Sale_Type</th>\n",
       "      <th>Sale_Condition</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>215000.0</td>\n",
       "      <td>One_Story_1946_and_Newer_All_Styles</td>\n",
       "      <td>Residential_Low_Density</td>\n",
       "      <td>141.0</td>\n",
       "      <td>31770.0</td>\n",
       "      <td>Pave</td>\n",
       "      <td>No_Alley_Access</td>\n",
       "      <td>Slightly_Irregular</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Pool</td>\n",
       "      <td>No_Fence</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>-93.619754</td>\n",
       "      <td>42.054035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>105000.0</td>\n",
       "      <td>One_Story_1946_and_Newer_All_Styles</td>\n",
       "      <td>Residential_High_Density</td>\n",
       "      <td>80.0</td>\n",
       "      <td>11622.0</td>\n",
       "      <td>Pave</td>\n",
       "      <td>No_Alley_Access</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>No_Pool</td>\n",
       "      <td>Minimum_Privacy</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>-93.619756</td>\n",
       "      <td>42.053014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sale_Price                          MS_SubClass                 MS_Zoning  \\\n",
       "0    215000.0  One_Story_1946_and_Newer_All_Styles   Residential_Low_Density   \n",
       "1    105000.0  One_Story_1946_and_Newer_All_Styles  Residential_High_Density   \n",
       "\n",
       "   Lot_Frontage  Lot_Area Street            Alley           Lot_Shape  \\\n",
       "0         141.0   31770.0   Pave  No_Alley_Access  Slightly_Irregular   \n",
       "1          80.0   11622.0   Pave  No_Alley_Access             Regular   \n",
       "\n",
       "  Land_Contour Utilities  ...  Pool_QC            Fence Misc_Feature Misc_Val  \\\n",
       "0          Lvl    AllPub  ...  No_Pool         No_Fence         None      0.0   \n",
       "1          Lvl    AllPub  ...  No_Pool  Minimum_Privacy         None      0.0   \n",
       "\n",
       "  Mo_Sold Year_Sold Sale_Type Sale_Condition  Longitude   Latitude  \n",
       "0     5.0    2010.0       WD          Normal -93.619754  42.054035  \n",
       "1     6.0    2010.0       WD          Normal -93.619756  42.053014  \n",
       "\n",
       "[2 rows x 81 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fetch the ames_housing data-set from openml using its data_id.\n",
    "df, y = fetch_openml(data_id=43926, return_X_y=True)\n",
    "\n",
    "# Add the target column to the other features.\n",
    "df.insert(0, y.name, y)\n",
    "print(f\"Shape: {df.shape}\")\n",
    "\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the target distribution.\n",
    "sns.set_theme(rc={\"figure.figsize\": (6, 3)})\n",
    "sns.displot(y, kde=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "35 numerical features vs 46 categorical features.\n"
     ]
    }
   ],
   "source": [
    "# Pick the numerical features of our data-set.\n",
    "float_columns = df.select_dtypes(include=[np.number]).columns\n",
    "categorical_columns = df.select_dtypes(include=\"category\").columns\n",
    "\n",
    "print(\n",
    "    f\"{len(float_columns)} numerical features vs {len(categorical_columns)} categorical features.\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This data-set is composed of $35$ numerical variables and $46$ categorical variables (which represent more than half of the features in our data-set). We can also note that the features are not in the same scale."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pre-processing\n",
    "\n",
    "Unlike linear models, decision trees require less data processing. Cases of missing values and outliers have less impact as tree models are not distance based, so they can handle varying ranges of features. Thus, there is no need for feature scaling (standardization or normalization). Moreover, tree-based models can handle categorical variables.\n",
    "\n",
    "However, we cannot apply our trees directly on categorical data. To convert these variables into numerical form, there are several approaches:\n",
    "\n",
    "**One Hot Encoding:** \n",
    "\n",
    "A binary representation, that creates $k-1$ additional dummy variables (DVs) where $k$ is the number of different values that the categorical variable can take. \n",
    "\n",
    "But trees perform poorly with this type of encoding, if the number of variables is big, because DVs induce sparsity into the data-set (many zeros, few ones). In addition, since tree algorithms use splits based on feature values and all the dummy variables are independent, if the tree decides to make a split on one of the DVs, there is only one possible split. Thus, the trees will generally tend to grow in the direction of the zeros. The splits are not optimal and the resulting tree will perform badly.\n",
    "\n",
    "**Label Encoding:**\n",
    "\n",
    "Label Encoding converts each value in a categorical column to a number. The numbers are assigned in increasing order.\n",
    "\n",
    "Label Encoding is most commonly used for categorical target variables that have some type of order in their values. \n",
    "\n",
    "When a large number of such categorical variables are present, and they have many unique values, in the case of tree-based models, Label Encoding of all categorical variables often provides a simple and sufficiently effective solution to encoding these values. \n",
    "\n",
    "Indeed with One Hot Encoding, the dimensionality of the data becomes too great and the resolution of one hot encoded variables is too low, as described above.\n",
    "\n",
    "In the following, we use the label encoding approach."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_encoded = df.copy()\n",
    "\n",
    "# Encode target labels with value between 0 and n_classes-1.\n",
    "le = preprocessing.LabelEncoder()\n",
    "# Convert the above categorical features into numeric type.\n",
    "df_encoded[categorical_columns] = df[categorical_columns].apply(le.fit_transform)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see what the new dataframe looks like after LabelEncoding:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MS_SubClass</th>\n",
       "      <th>MS_Zoning</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot_Shape</th>\n",
       "      <th>Land_Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>Lot_Config</th>\n",
       "      <th>Land_Slope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>...</th>\n",
       "      <th>Garage_Type</th>\n",
       "      <th>Garage_Finish</th>\n",
       "      <th>Garage_Qual</th>\n",
       "      <th>Garage_Cond</th>\n",
       "      <th>Paved_Drive</th>\n",
       "      <th>Pool_QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc_Feature</th>\n",
       "      <th>Sale_Type</th>\n",
       "      <th>Sale_Condition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>One_Story_1946_and_Newer_All_Styles</td>\n",
       "      <td>Residential_Low_Density</td>\n",
       "      <td>Pave</td>\n",
       "      <td>No_Alley_Access</td>\n",
       "      <td>Slightly_Irregular</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>North_Ames</td>\n",
       "      <td>...</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>Fin</td>\n",
       "      <td>Typical</td>\n",
       "      <td>Typical</td>\n",
       "      <td>Partial_Pavement</td>\n",
       "      <td>No_Pool</td>\n",
       "      <td>No_Fence</td>\n",
       "      <td>None</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>One_Story_1946_and_Newer_All_Styles</td>\n",
       "      <td>Residential_High_Density</td>\n",
       "      <td>Pave</td>\n",
       "      <td>No_Alley_Access</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>North_Ames</td>\n",
       "      <td>...</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>Unf</td>\n",
       "      <td>Typical</td>\n",
       "      <td>Typical</td>\n",
       "      <td>Paved</td>\n",
       "      <td>No_Pool</td>\n",
       "      <td>Minimum_Privacy</td>\n",
       "      <td>None</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           MS_SubClass                 MS_Zoning Street  \\\n",
       "0  One_Story_1946_and_Newer_All_Styles   Residential_Low_Density   Pave   \n",
       "1  One_Story_1946_and_Newer_All_Styles  Residential_High_Density   Pave   \n",
       "\n",
       "             Alley           Lot_Shape Land_Contour Utilities Lot_Config  \\\n",
       "0  No_Alley_Access  Slightly_Irregular          Lvl    AllPub     Corner   \n",
       "1  No_Alley_Access             Regular          Lvl    AllPub     Inside   \n",
       "\n",
       "  Land_Slope Neighborhood  ... Garage_Type Garage_Finish Garage_Qual  \\\n",
       "0        Gtl   North_Ames  ...      Attchd           Fin     Typical   \n",
       "1        Gtl   North_Ames  ...      Attchd           Unf     Typical   \n",
       "\n",
       "  Garage_Cond       Paved_Drive  Pool_QC            Fence Misc_Feature  \\\n",
       "0     Typical  Partial_Pavement  No_Pool         No_Fence         None   \n",
       "1     Typical             Paved  No_Pool  Minimum_Privacy         None   \n",
       "\n",
       "  Sale_Type Sale_Condition  \n",
       "0       WD          Normal  \n",
       "1       WD          Normal  \n",
       "\n",
       "[2 rows x 46 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Before data transformation:\n",
    "df[categorical_columns].head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MS_SubClass</th>\n",
       "      <th>MS_Zoning</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot_Shape</th>\n",
       "      <th>Land_Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>Lot_Config</th>\n",
       "      <th>Land_Slope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>...</th>\n",
       "      <th>Garage_Type</th>\n",
       "      <th>Garage_Finish</th>\n",
       "      <th>Garage_Qual</th>\n",
       "      <th>Garage_Cond</th>\n",
       "      <th>Paved_Drive</th>\n",
       "      <th>Pool_QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc_Feature</th>\n",
       "      <th>Sale_Type</th>\n",
       "      <th>Sale_Condition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   MS_SubClass  MS_Zoning  Street  Alley  Lot_Shape  Land_Contour  Utilities  \\\n",
       "0            2          5       1      1          3             3          0   \n",
       "1            2          4       1      1          2             3          0   \n",
       "\n",
       "   Lot_Config  Land_Slope  Neighborhood  ...  Garage_Type  Garage_Finish  \\\n",
       "0           0           0            15  ...            0              0   \n",
       "1           4           0            15  ...            0              3   \n",
       "\n",
       "   Garage_Qual  Garage_Cond  Paved_Drive  Pool_QC  Fence  Misc_Feature  \\\n",
       "0            5            5            1        3      4             2   \n",
       "1            5            5            2        3      2             2   \n",
       "\n",
       "   Sale_Type  Sale_Condition  \n",
       "0          9               4  \n",
       "1          9               4  \n",
       "\n",
       "[2 rows x 46 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# After data transformation:\n",
    "df_encoded[categorical_columns].head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Split the data into a training set and a test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing the target column from the dataframe.\n",
    "X = df_encoded.drop(columns=y.name, axis=1, inplace=False)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.1, shuffle=True, random_state=24\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Baseline: a floating point clear-data XGB regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Common hyper-parameters for both scikit-learn and Concrete ML.\n",
    "n_estimators = 50\n",
    "max_depth = 4\n",
    "n_jobs = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Training and prediction with XGBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_score with XGBoost: 0.92\n"
     ]
    }
   ],
   "source": [
    "# 1. Instantiation of the model.\n",
    "xgboost_reg = SklearnXGBRegressor(n_estimators=n_estimators, max_depth=max_depth, n_jobs=n_jobs)\n",
    "\n",
    "# 2. Train the model.\n",
    "xgboost_reg.fit(X_train, y_train)\n",
    "\n",
    "# 3. XGBoost (fp32) predictions:\n",
    "y_preds_XGBoost = xgboost_reg.predict(X_test)\n",
    "\n",
    "# 4. Evaluation of the with r2_score metric.\n",
    "print(f\"R2_score with XGBoost: {metrics.r2_score(y_test, y_preds_XGBoost):.2f}\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Concrete ML XGB regressor\n",
    "\n",
    "The typical development flow of a Concrete ML model is the following:\n",
    "\n",
    "1. The model is trained on clear (plaintext) data\n",
    "    + Concrete ML currently only supports inference in FHE; training is done on clear data\n",
    "\n",
    "2. Since FHE operates only over integers, the resulting trained model is quantized. To do so, you need to set `n_bits` parameter\n",
    "\n",
    "    + note that the current version of Concrete ML has a precision limitation of 16-bits, i.e., it doesn't support encrypted values larger than 16-bits integers. So, if you encounter this error: `RuntimeError: Function you are trying to compile cannot be converted to MLIR` during compilation, decrease the number of bits.\n",
    "\n",
    "3. The quantized model is compiled to an FHE equivalent. The compilation step can be broken up into 3 parts \n",
    "that are performed automatically by Concrete ML:\n",
    "\n",
    "    + creation of an executable operation graph\n",
    "    + checking that the operation graph is FHE compatible, i.e., checking the maximum bit-width needed to execute the model\n",
    "    + determining cryptographic parameters that will help to generate the secret keys and evaluation keys\n",
    "\n",
    "4. Once, the model is compiled to an FHE equivalent, inference can then be done on:\n",
    "    + encrypted data, by setting `fhe` to `execute`\n",
    "    + clear data, using the quantized model, by setting `fhe` to `disable`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating a key for an 7-bits circuit\n",
      "Key generation time: 0.964 sec\n"
     ]
    }
   ],
   "source": [
    "# 1. Instantiation of the model, the only difference is the `n_bits` hyper-parameter.\n",
    "# We quantize the inputs and the weights using `n_bits` because FHE operates only over integers\n",
    "\n",
    "# n_bits is necessary for the XGBoost of Concrete ML.\n",
    "n_bits = 5\n",
    "\n",
    "concrete_reg = ConcreteXGBRegressor(\n",
    "    n_bits=n_bits, n_estimators=n_estimators, max_depth=max_depth, n_jobs=n_jobs\n",
    ")\n",
    "\n",
    "# 2. We train the concrete XGBoost model on clear data.\n",
    "concrete_reg.fit(X_train, y_train)\n",
    "\n",
    "# 3. Compilation:\n",
    "# The quantized model is compiled to an FHE equivalent. To do so, the compiler requires\n",
    "# an exhaustive set of data to mainly evaluate the maximum integer bit-width within the graph,\n",
    "# needed during the FHE computations.\n",
    "circuit = concrete_reg.compile(X_train)\n",
    "print(f\"Generating a key for an {circuit.graph.maximum_integer_bit_width()}-bits circuit\")\n",
    "\n",
    "# Key generation:\n",
    "# The compiler returns a circuit, which can then be used for the key generation.\n",
    "time_begin = time.time()\n",
    "circuit.client.keygen(force=False)\n",
    "print(f\"Key generation time: {(time.time() - time_begin):.3f} sec\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature importances\n",
    "\n",
    "An advantage of using decision trees is that once the trees are constructed, we can retrieve the importance scores of each attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "width = 0.2\n",
    "n_features = 5  # or X.shape[1] to get all importance scores of each attributes\n",
    "feature_names = X.columns\n",
    "\n",
    "# Retrieving the feature importances.\n",
    "concrete_feature_importances = concrete_reg.sklearn_model.feature_importances_\n",
    "xgboost_feature_importances = xgboost_reg.feature_importances_\n",
    "\n",
    "# Sorting the feature_importances_ according the XGBoost results.\n",
    "index_importances = [[i, fi] for i, fi in enumerate(xgboost_feature_importances)]\n",
    "index_importances_sorted = np.array(\n",
    "    sorted(index_importances, key=lambda key: key[1], reverse=True)\n",
    ")[:, 0]\n",
    "\n",
    "# Displaying the 5 highest feature importances.\n",
    "index_importances_sorted = list(map(int, index_importances_sorted))[:n_features]\n",
    "\n",
    "_, ax = plt.subplots(figsize=(10, 2))\n",
    "\n",
    "ax.barh(\n",
    "    range(n_features),\n",
    "    xgboost_feature_importances[index_importances_sorted],\n",
    "    width,\n",
    "    color=\"red\",\n",
    "    label=\"XGBoost\",\n",
    ")\n",
    "ax.barh(\n",
    "    np.arange(n_features) + width,\n",
    "    concrete_feature_importances[index_importances_sorted],\n",
    "    width,\n",
    "    color=\"green\",\n",
    "    label=\"XGBoost - Concrete ML\",\n",
    ")\n",
    "\n",
    "ax.set_title(\"Feature importances according to Concrete ML model and scikit-learn model\", size=12)\n",
    "ax.set_yticks(range(n_features), feature_names[index_importances_sorted][:n_features])\n",
    "ax.set_xlabel(\"Feature importances\")\n",
    "ax.set_ylabel(\"Features name\")\n",
    "\n",
    "ax.legend(loc=\"best\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both models give relatively the same importance scores."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference with Concrete ML:\n",
    "\n",
    "As mentioned above, you can perform inference in two ways :\n",
    "\n",
    "a. __Simulation__: inference on clear data using Concrete ML, without secure FHE execution. \n",
    "\n",
    "b. __Execution in FHE__: inference on encrypted data, using FHE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulation: inference on clear data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 4.1 Inference on clear quantized data (fhe=\"disable\"), the execution is very fast.\n",
    "y_preds_non_fhe = concrete_reg.predict(X_test, fhe=\"disable\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's see the predictions of the quantized XGBoost model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_predictions(y_true: np.array, y_preds: dict, colors: list) -> None:\n",
    "    # For a better visualization, we sort the predictions and the ground truth.\n",
    "    y_true = np.array(y_true)\n",
    "    idx = np.argsort(y_true)\n",
    "    y_true_sorted = y_true[idx]\n",
    "\n",
    "    for title, y_pred in y_preds.items():\n",
    "        y_preds[title] = y_pred[idx].flatten()\n",
    "\n",
    "    ncols, nrows = len(y_preds), 1\n",
    "\n",
    "    fig, axes = plt.subplots(nrows, ncols, figsize=(15, 5))\n",
    "\n",
    "    for i, ((title, y_pred), c) in enumerate(zip(y_preds.items(), colors)):\n",
    "        axes[i].scatter(np.arange(len(y_true_sorted)), y_true_sorted, c=\"r\")\n",
    "        axes[i].scatter(np.arange(len(y_true_sorted)), y_pred, c=c, alpha=0.5)\n",
    "        axes[i].set_xlabel(title, labelpad=5)\n",
    "        axes[i].set_ylabel(\"Sale_Prices ($)\")\n",
    "        # Hide x ticks, because it just refers to indexes.\n",
    "        axes[i].get_xaxis().set_ticks([])\n",
    "\n",
    "    # Set the spacing between subplots.\n",
    "    fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_score with XGBoost: 0.9233\n",
      "R2_score in FHE simulation (not encrypted): 0.8994\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(\n",
    "    y_test,\n",
    "    y_preds={\"XGBoost\": y_preds_XGBoost, \"Quant. XGBoost\": y_preds_non_fhe},\n",
    "    colors=[\"g\", \"b\"],\n",
    ")\n",
    "\n",
    "print(f\"R2_score with XGBoost: {metrics.r2_score(y_test, y_preds_XGBoost):.4f}\")\n",
    "print(\n",
    "    f\"R2_score in FHE simulation (not encrypted): {metrics.r2_score(y_test, y_preds_non_fhe):.4f}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference in FHE\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Design Space Exploration\n",
    "\n",
    "\n",
    "Since the execution time in FHE can be long, a good practice is to find a good compromise between `n_estimators` and `n_bits` in order to obtain good performance while keeping these parameters low. The run-time of the XGB classifier\n",
    "is strongly related to the values of these parameters (lower values give faster execution).\n",
    "\n",
    "To find this parameter combination, grid search can be used using the sklearn `GridSearchCV` class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_folds = 5\n",
    "param_grid = {\n",
    "    \"n_bits\": [2, 3, 4, 5, 6, 7],\n",
    "    \"max_depth\": [4],\n",
    "    \"n_estimators\": [10, 20, 50, 100],\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_search_concrete = GridSearchCV(ConcreteXGBRegressor(), param_grid, cv=n_folds, n_jobs=1)\n",
    "grid_search_concrete.fit(X_train, y_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best score : 0.888\n",
      "Best params: {'max_depth': 4, 'n_bits': 7, 'n_estimators': 50}\n"
     ]
    }
   ],
   "source": [
    "results = pd.DataFrame(grid_search_concrete.cv_results_)\n",
    "\n",
    "print(f\"Best score : {grid_search_concrete.best_score_:.3f}\")\n",
    "print(f\"Best params: {grid_search_concrete.best_params_}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Impact of running in FHE:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lineplot(df, yaxis, ylabel, title, group_keys: str = \"param_n_estimators\"):\n",
    "    params = [\n",
    "        {\"color\": \"red\", \"linewidth\": 1},\n",
    "        {\"color\": \"green\", \"marker\": \"x\", \"markersize\": 5, \"linewidth\": 1},\n",
    "        {\"color\": \"magenta\", \"marker\": \"s\", \"markersize\": 5, \"dashes\": (3, 20)},\n",
    "        {\"color\": \"blue\", \"marker\": \"^\", \"markersize\": 5, \"dashes\": (3, 10)},\n",
    "        {\"color\": \"gold\", \"marker\": \"*\", \"markersize\": 5, \"dashes\": (3, 40)},\n",
    "        {\"color\": \"black\", \"linestyle\": \"dashed\", \"dashes\": (3, 10)},\n",
    "    ]\n",
    "\n",
    "    plt.figure(figsize=(15, 4))\n",
    "\n",
    "    for (key, grp), param in zip(df.groupby([group_keys]), params):\n",
    "        plt.plot(grp[\"param_n_bits\"], grp[yaxis], **param, label=f\"estimators_{key}\")\n",
    "\n",
    "    plt.title(title)\n",
    "    plt.ylabel(ylabel)\n",
    "    plt.xlabel(\"$n_{bits}$\")\n",
    "    plt.legend(loc=\"best\")\n",
    "    plt.ylim(0, 1)\n",
    "    plt.minorticks_on()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Score according to n_bits, n_estimators and max_depth parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lineplot(\n",
    "    df=results,\n",
    "    yaxis=\"mean_test_score\",\n",
    "    ylabel=\"$r^2_{score}$\",\n",
    "    title=\"$r^2_{score}$ given n_estimators and n_bits\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given a data-set of $2930$ examples and $81$ features.\n",
    "\n",
    "As we can see in the graphs above: the higher the `n_bits` and `n_estimators`, the better the results. But the execution time also increases.\n",
    "So, to keep this notebook fast, we manually choose the best combination of parameters: `n_estimators = 50, n_bits = 5`. Larger values for these parameters do not seem to provide a decrease in regression error (i.e., the R²_score does not increase). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_params_xgboost = {\"n_estimators\": 50, \"n_bits\": 5}\n",
    "\n",
    "# Train the concrete xgboost with the best combination of parameters.\n",
    "concrete_reg = ConcreteXGBRegressor(**best_params_xgboost, n_jobs=1)\n",
    "\n",
    "concrete_reg.fit(X_train, y_train)\n",
    "\n",
    "from concrete.compiler import check_gpu_available\n",
    "\n",
    "use_gpu_if_available = False\n",
    "device = \"cuda\" if use_gpu_if_available and check_gpu_available() else \"cpu\"\n",
    "\n",
    "# Compile the model using the training data.\n",
    "circuit = concrete_reg.compile(X_train, device=device)\n",
    "\n",
    "# Get the equivalent predictions in clear quantized data:\n",
    "y_preds_clear = concrete_reg.predict(X_test, fhe=\"disable\")\n",
    "\n",
    "# Perform the inference in FHE (simulation):\n",
    "y_preds_simulated = concrete_reg.predict(X_test, fhe=\"simulate\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(\n",
    "    y_test,\n",
    "    y_preds={\n",
    "        \"XGBoost\": y_preds_XGBoost,\n",
    "        \"Concrete ML without FHE\": y_preds_clear,\n",
    "        \"Concrete ML with FHE (simulation)\": y_preds_simulated,\n",
    "    },\n",
    "    colors=[\"g\", \"b\", \"m\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FHE runtime per sample: 0.72 sec\n"
     ]
    }
   ],
   "source": [
    "# Test in FHE on a smaller test set\n",
    "FHE_SAMPLE = 20\n",
    "X_test_fhe = X_test[:FHE_SAMPLE]\n",
    "y_test_fhe = y_test[:FHE_SAMPLE]\n",
    "\n",
    "# Perform the inference in FHE:\n",
    "time_begin = time.time()\n",
    "y_preds_fhe = concrete_reg.predict(X_test_fhe, fhe=\"execute\")\n",
    "print(f\"FHE runtime per sample: {(time.time() - time_begin) / len(X_test_fhe):.2f} sec\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_score with XGBoost            : 0.9233\n",
      "R2_score without FHE             : 0.9005\n",
      "R2_score with FHE (simulation)   : 0.9005\n",
      "R2_score with FHE                : 0.9036\n"
     ]
    }
   ],
   "source": [
    "# Evaluation\n",
    "\n",
    "r2_score_sklearn = metrics.r2_score(y_test, y_preds_XGBoost)\n",
    "r2_score_clear_concrete = metrics.r2_score(y_test, y_preds_clear)\n",
    "r2_score_simulated_concrete = metrics.r2_score(y_test, y_preds_simulated)\n",
    "r2_score_fhe_concrete = metrics.r2_score(y_test_fhe, y_preds_fhe)\n",
    "\n",
    "print(f\"R2_score with XGBoost            : {r2_score_sklearn:.4f}\")\n",
    "print(f\"R2_score without FHE             : {r2_score_clear_concrete:.4f}\")\n",
    "print(f\"R2_score with FHE (simulation)   : {r2_score_simulated_concrete:.4f}\")\n",
    "print(f\"R2_score with FHE                : {r2_score_fhe_concrete:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As can be seen in this graph and in the R2 metric value, the predictions with and without an FHE execution are the same and the concrete XGBoost model is just as good as the XGBoost model (within a small error margin). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conclusion\n",
    "\n",
    "This tutorial, has shown how easy it is to build, train, and evaluate an XGBoost model using the Concrete ML library.\n",
    "\n",
    "The results of the Concrete ML model are as good as those of the XGBoost model and execution in FHE is correct  with respect to the simulation results. \n",
    "\n",
    "The strong similarity between the XGBoost and Concrete ML was discussed and the tutorial presented the typical development flow of a Concrete ML model. \n",
    "\n",
    "The final regression model achieves an R2_score of $0.9$ and has a runtime on the order of several seconds."
   ]
  }
 ],
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